Basics of meta-analysis:I2is not an absolute measure of heterogeneity
| Autor: | Hannah R. Rothstein, Michael Borenstein, Julian P T Higgins, Larry V. Hedges |
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| Rok vydání: | 2017 |
| Předmět: |
Measure (mathematics)
Education 03 medical and health sciences Range (mathematics) 0302 clinical medicine Absolute (philosophy) Intervention (counseling) Meta-analysis Econometrics Statistical analysis 030212 general & internal medicine 030217 neurology & neurosurgery Statistic Mathematics Cognitive psychology |
| Zdroj: | Research Synthesis Methods. 8:5-18 |
| ISSN: | 1759-2879 |
| DOI: | 10.1002/jrsm.1230 |
| Popis: | When we speak about heterogeneity in a meta-analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention yields a mean effect size of 50 points, we want to know if the effect size in different populations varies from 40 to 60, or from 10 to 90, because this speaks to the potential utility of the intervention. While there is a common belief that the I2 statistic provides this information, it actually does not. In this example, if we are told that I2 is 50%, we have no way of knowing if the effects range from 40 to 60, or from 10 to 90, or across some other range. Rather, if we want to communicate the predicted range of effects, then we should simply report this range. This gives readers the information they think is being captured by I2 and does so in a way that is concise and unambiguous. Copyright © 2017 John Wiley & Sons, Ltd. |
| Databáze: | OpenAIRE |
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